Approximately 80% of stroke patients experience acute hemiparesis and approximately 40% have chronic hemiparesis. This impairment significantly limits functional use of the arm. Traditionally, hemiparesis has been characterized by weakness, spasticity and unwanted synergies. These abnormalities are usually assessed using clinical scales. Here we propose to approach the problem of hemiparesis from a more quantitative and modular motor control perspective. Our previous work, investigating planar reaching movements in healthy young subjects, demonstrates that accurate reaching depends en two types of visuomotor transformation. The first transforms a visual target into a planned trajectory in vectorial space centered at the hand with independent specification of direction and extent. This spatial transformation requires the learning of a task-specific reference frame and scaling factor. Once a plan in extrinsic coordinates is determined, a second transformation generates the required torques in intrinsic (joint) coordinates. This dynamic transformation requires learning of the biomechanical properties of the limb. The principal hypothesis of this proposal is that patients with hemiparesis have impairments in using and learning visuomotor transformations. Our secondary hypotheses are that there will be differential impairments in these visuomotor transformations depending on whether the dominant or non-dominant arm is affected and on lesion location. We will include patients who are six months or more out from their first stroke with clinically demonstrable arm weakness at stroke onset. All patients in the study will have had a structural brain MRI with diffusion and perfusion-weighted imaging. Patients with more than one lesion or inability to follow instructions will be excluded. Patients (and age-matched controls) will perform planar reaching movements with their arm supported on a horizontal surface to eliminate gravity. Hand position and joint angle data will be obtained using a magnetic recording system. Motor learning will be assessed by having subjects adapt to a cursor rotation or a laterally-placed mass. Lesion location will be determined by a neuroradiologist. Confirmation of common lesion locations across patients will be made by transforming the T1 images into Tailarach space using SPM2. Our findings will contribute to a mechanistic understanding of hemiparesis, suggest novel rehabilitation strategies and help find better measures of recovery.